使用双卡尔曼滤波器进行运动预测以实现稳健的跳动心脏跟踪。

Motion prediction using dual Kalman filter for robust beating heart tracking.

作者信息

Yang Bo, Liu Chao, Poignet Philippe, Zheng Wenfeng, Liu Shan

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2015 Aug;2015:4875-8. doi: 10.1109/EMBC.2015.7319485.

DOI:10.1109/EMBC.2015.7319485

Abstract

A novel prediction method for robust beating heart tracking is proposed. The dual time-varying Fourier series is used to model the heart motion. The frequency parameters and Fourier coefficients in the model are estimated respectively by using a dual Kalman filter scheme. The instantaneous frequencies of breathing and heartbeat motion are measured online from the 3D trajectory of the point of interest using an orthogonal decomposition algorithm. The proposed method is evaluated based on both the simulated signals and the real motion signals, which are measured from the videos recorded using the da Vinci surgical system.

摘要

提出了一种用于稳健跳动心脏跟踪的新型预测方法。采用双时变傅里叶级数对心脏运动进行建模。利用双卡尔曼滤波方案分别估计模型中的频率参数和傅里叶系数。使用正交分解算法从感兴趣点的三维轨迹在线测量呼吸和心跳运动的瞬时频率。基于模拟信号和真实运动信号对所提出的方法进行评估，这些信号是从使用达芬奇手术系统录制的视频中测量得到的。